Vol.:(0123456789)1 3

Abdominal Radiology https://doi.org/10.1007/s00261-021-03190-w

SPECIAL SECTION: QUANTITATIVE

Quantitative CT perfusion imaging in patients with pancreatic cancer: a systematic review

T. H. Perik1  · E. A. J. van Genugten1 · E. H. J. G. Aarntzen1 · E. J. Smit1 · H. J. Huisman1 · J. J. Hermans1

Received: 16 April 2021 / Revised: 18 June 2021 / Accepted: 21 June 2021 © The Author(s) 2021

AbstractPancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related death with a 5-year survival rate of 10%. Quantitative CT perfusion (CTP) can provide additional diagnostic information compared to the limited accuracy of the current standard, contrast-enhanced CT (CECT). This systematic review evaluates CTP for diagnosis, grading, and treatment assessment of PDAC. The secondary goal is to provide an overview of scan protocols and perfusion models used for CTP in PDAC. The search strategy combined synonyms for ‘CTP’ and ‘PDAC.’ Pubmed, Embase, and Web of Science were systematically searched from January 2000 to December 2020 for studies using CTP to evaluate PDAC. The risk of bias was assessed using QUADAS-2. 607 abstracts were screened, of which 29 were selected for full-text eligibility. 21 studies were included in the final analysis with a total of 760 patients. All studies comparing PDAC with non-tumorous parenchyma found significant CTP-based differences in blood flow (BF) and blood volume (BV). Two studies found significant differ-ences between pathological grades. Two other studies showed that BF could predict neoadjuvant treatment response. A wide variety in kinetic models and acquisition protocol was found among included studies. Quantitative CTP shows a potential benefit in PDAC diagnosis and can serve as a tool for pathological grading and treatment assessment; however, clinical evidence is still limited. To improve clinical use, standardized acquisition and reconstruction parameters are necessary for interchangeability of the perfusion parameters.

Graphic abstract

Keywords CT perfusion · Adenocarcinoma · Pancreas · Quantitative imaging

Introduction

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related death in the USA [1]. The incidence increases by an estimated 0.5% per year, while prognosis remains poor, with a 5-year survival rate of 10%

* T. H. Perik tom.perik@radboudumc.nl

1 Department of Medical Imaging, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands

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[1]. Availability and advancement of imaging technology and new treatment options have not improved 5-year survival in the last 40 years, mainly due to late presentation [2]. As 40% presents with locally advanced disease and 40–45% with metastatic disease, the majority of patients face incur-able disease [3].

Biphasic or triphasic contrast-enhanced CT (CECT), with at least both an arterial and portal-venous phase, is the cur-rent standard for diagnosis, assessment of resectability, and monitoring of therapy of PDAC [4]. However, several prob-lems are currently encountered using CECT. First, tumor characterization and delineation, essential for staging and pre-operative planning, are not always possible. Accurate diagnosis based on CECT is difficult as tumors may appear isoattenuating to the surrounding parenchyma in 15–20% of cases [5, 6]. In addition, inflammatory masses of acute and chronic pancreatitis can mimic PDAC on CECT, risking misdiagnosis [7]. Second, histopathological analysis is the gold standard, and tumor grading is an important parameter of survival [8]. However, biopsies do not always yield suf-ficient material for pathological grade analysis. With fine-needle biopsy (FNB), accurate histology is retrieved in 77% of all procedures, at the risk of complications [9]. Further-more, as PDAC is a heterogeneous tumor, biopsy could lead to a sampling error [10]. A noninvasive, reliable imaging biomarker would be highly desirable to accurately assess the histological grading of the complete tumor, which could aid in selecting patients for the appropriate treatment. Third, with the current imaging techniques, RECIST-based treat-ment assessment is insufficient. Neoadjuvant chemotherapy is increasingly applied for potential resectable PDAC [11]. However, RECIST-based restaging remains troublesome because changes in tumor size and vessel encasement using CECT prove to be inadequate for reliable response assess-ment after neoadjuvant treatment [12]. Moreover, the cor-relation between RECIST and histopathological grading of tumor response is poor [13]. Thus, CECT response criteria could underestimate the treatment response, showing the need for a more reliable predictor to increase the amount of margin-negative resections (i.e., R0).

CT perfusion (CTP), in other words dynamic contrast-enhanced CT, is a novel modality that could improve the diagnostic workup of PDAC by combining functional infor-mation and spatial detail [14]. CTP is an imaging technique where dynamic acquisition after injection of a contrast agent enables quantification of tissue vascularization [15]. Using a kinetic model, parameters can be calculated, which reflect intratumoral differences in perfusion and vascular perme-ability. Therefore, CTP bears potential as a biomarker in oncology for tumor angiogenesis, enabling prediction of tumor grading and assessment of treatment response [16–19]. Over the last years, CTP is increasingly utilized as a functional imaging biomarker, and several articles

reported additional benefits and advances of CTP in pan-creatic cancer.

This systematic review aims to evaluate the literature on CTP in pancreatic cancer for diagnosis, grading, and treat-ment assessment. The secondary goal is to provide an over-view of scan protocols and perfusion models used for CTP in the pancreas.

Materials and methods

Search strategy

This systematic review was carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis 2015 (Prisma-P 2015) [20]. The protocol for this systematic review is registered in the PROSPERO data-base [Registration number: CRD42021213438] [21]. The search strategy combined synonyms for ‘CTP,’ ‘Dynamic contrast-enhanced CT,’ ‘Pancreatic cancer,’ and ‘Pancreatic adenocarcinoma’; the complete search is accessible in the Supplementary materials. This systematic search was per-formed in the following libraries: PubMed, EMBASE, and Web of Science; search terms were tailored to each database. The timeframe for published articles was 1 January 2000–31 December 2020.

Eligibility criteria

Studies were considered eligible when CTP was used dur-ing diagnosis or treatment assessment of primary PDAC. The scan protocol must be described clearly and consists of dynamic acquisitions resulting in calculated perfusion parameters, such as blood flow (BF), blood volume (BV), and permeability surface area product (PS).

Study selection

Retrieved articles were imported into EndNote and dupli-cates removed. The article titles and abstracts resulting from the search were screened independently by two reviewers (T.P, E.G.). Studies meeting the inclusion criteria were selected for full-text screening and reviewed. In the sub-sequent full-text screening stage, any disagreements were resolved by consensus, and if consensus was not reached, a third reviewer (J.H.) was consulted.

Data extraction/synthesis

Relevant study characteristics and scan parameters were extracted by one reviewer and checked by the second reviewer. Scan parameters included type of detector, num-ber of acquisitions, contrast injection, and type of kinetic

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model. Comparison of studies was performed using perfu-sion values such as BF, BV, and PS. To compare different studies, perfusion parameters were converted to mL/100 g/min when reported in mL/100 mL/min using a tissue density of 1.05 gr/mL [15]. Due to heterogeneity in the data, only descriptive statistic were applied. Studies were categorized based on the goal of the study and the type of kinetic model. Graphs were created using GraphPad Prism 9.

Quality assessment

The risk of bias and applicability of each study were assessed using the Quality Assessment of Diagnostic Accu-racy Studies (QUADAS-2) tool. The risk of bias and appli-cability concerns is defined as the risk to deviate from the QUADAS-2 guidelines described in four domains: patient selection, index test, reference standard, and flow and tim-ing. QUADAS signal questions regarding index test were adjusted to classify description of perfusion scan protocol, kinetic model software, and ROI measurement. Consensus about the assessment was reached between the same two reviewers who selected studies for inclusion.

Results

Study selection

With the described search strategy, 881 articles were iden-tified, which were reduced to 607 articles after removing duplicates. 607 articles were screened by title and abstracts, resulting in 29 articles eligible for full-text screening. Eight full-text articles were excluded as they did not meet the final inclusion criteria. Finally, 21 articles were included in the qualitative analysis, with a total of 760 patients with PDAC. All included studies with scan parameters and kinetic mod-els can be found in Table 1, and study characteristics can be found in Table 2.

The Prisma-2015 flowchart describing the selection pro-cess is visible in Fig. 1.

Diagnosis

In 15 out of 21 studies, BF was measured in both PDAC and non-tumorous pancreatic parenchyma, including a total of 519 patients. In all these studies, mean blood flow was significantly lower in tumor tissue compared to pancreatic parenchyma outside the tumor or in healthy pancreatic tis-sue in a control group [22–37]. Mean BF ranged from 17 to 60 mL/100 g/min for PDAC and 71–164 mL/100 g/min for pancreatic parenchyma. All mean BF values can be found in Fig. 2.

In 11 studies, BV was measured for PDAC and non-tumorous pancreatic parenchyma for a total of 423 patients. [22–24, 26, 30, 32, 33, 35–38]. In all of these studies a sta-tistically significantly lower mean BV was found for PDAC compared to pancreatic parenchyma outside the tumor. Mean BV ranged from 2.8 to 59 mL/100 g for PDAC and 15–200 mL/100 g for pancreatic parenchyma. All mean BV values can be found in Fig. 3.

In 9 studies, permeability surface product (PS) was meas-ured for both PDAC and non-tumorous pancreatic paren-chyma in a total of 349 patients. In all these studies, the mean permeability was lower in pancreatic tumor tissue [22, 23, 25, 26, 30, 32, 33, 35, 36]. In two studies, this difference was statistically significant [22, 33]. Mean PS for PDAC ranged from 11 to 38 mL/100 g/min and for non-tumorous pancreatic parenchyma from 20 to 56 mL/100 g/min. All mean PS values can be found in Fig. 4.

Aslan et al. and Delrue et al. showed a decrease in perfu-sion (BF and BV) for both chronic pancreatitis and PDAC. However, compared to acute and chronic pancreatitis, the BF and BV were significantly lower (p < 0.01) in PDAC, even for isoattenuating PDAC [22, 37]. Yadav reported that 6/42 lesions isoattenuating on CECT were visible on perfu-sion color maps. For differentiating PDAC from pancreatitis Yadav et al. report an AUC of 0.83 for BF and 0.80 for BV [33]. Aslan reports both sensitivity and specificity of 100% for BF and BV by using optimal cutoff values [22].

Some studies also assessed semi-quantitative parameters such as peak enhancement and mean transit time (MTT). Peak enhancement showed in two studies to be significantly higher in pancreatic parenchyma than in PDAC (Lu: 30.8 vs 57 HU p < 0.016, Tan: 59 vs 101 HU p < 0.001) [31, 34]. In two other studies, MTT was significantly higher in PDAC compared to healthy pancreatic parenchyma [Aslan: 11.2 vs. 3.7 s, (p < 0.001), Kovac: 7.4 vs. 4 s (p < 0.001)] [22, 24].

Grading

Three articles evaluate the use of CTP to predict histopatho-logical grading of PDAC compared to histopathological diagnosis obtained using a tumor biopsy or resected speci-men [24, 39, 40]. These three studies included a total of 124 patients [24, 39, 40].

In two articles, tumors were classified into two groups: low grade (well or moderate differentiated) and high grade (poorly differentiated) [24, 40]. Both studies found higher BV in low-grade tumors compared to high-grade tumors (p = 0.001 and p = 0.004), whereas a significant difference in BF was only reported by one article (p = 0.041). Further-more, peak enhancement intensity compared to baseline HU was significantly different between high-grade tumors and low-grade tumors, respectively, 16 HU vs. 26 HU. Time to peak (TTP) did not show a significant difference between

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Tabl

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Ove

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w o

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d stu

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with

repo

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pub-

licat

ion

year

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tatio

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Con

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c-tio

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Mul

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e de

tect

or

(z-c

over

age)

kVp

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umbe

r of

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ons

(sca

n tim

e)

Scan

del

ayK

inet

ic m

odel

Softw

are

(ven

-do

r)RO

I (si

ze)

Bre

athi

ng

Asl

an e

t al.

2018

, [22

]50

 mL

with

5 

mL/

s64

slic

e (1

10 m

m)

100

100

242

slic

es

(126

 s)0 

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volu

tion

Syng

o M

MW

P (S

iem

ens)

Circ

ular

RO

I (1

5mm

2 )Sh

allo

w b

reat

hing

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et a

l. 20

19,

[30]

50 m

L w

ith

5 m

L/s

64 sl

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(84 

mm

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200

17 a

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men

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Abdominal Radiology

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Abdominal Radiology

1 3

Tabl

e 2

Stu

dy c

hara

cter

istic

s

Aut

hor,

publ

icat

ion

year

, ci

tatio

nPa

tient

s with

PD

AC

(n =

)A

imC

oncl

usio

nC

ateg

ory

Rad

iatio

n do

se (m

Sv)

Gol

d st

anda

rd

Asl

an e

t al.

2018

, [22

]61

Diff

eren

tiate

PD

AC

from

pa

ncre

atiti

s in

isoa

ttena

ut-

ing

tum

ors u

sing

CTP

BV, B

F, a

nd P

S ar

e si

g-ni

fican

tly lo

wer

in P

DA

C

com

pare

d to

pan

crea

tic

pare

nchy

ma.

Sho

win

g C

TP

is u

sefu

l for

dia

gnos

is

Dia

gnos

is6.

3 ± 2.

1Pa

thol

ogy

Bao

et a

l. 20

19, [

30]

30Ev

alua

te th

e co

rrel

atio

n of

du

al-e

nerg

y C

T io

dine

m

aps w

ith C

TP in

pat

ient

s su

spec

ted

of P

DA

C

Iodi

ne m

aps a

re re

late

d to

B

F an

d BV

obt

aine

d in

C

TP. D

iagn

ostic

sens

itiv-

ity is

low

er in

iodi

ne m

aps

com

pare

d to

CTP

Dia

gnos

is, s

can

tech

niqu

e8.

6Pa

thol

ogy

Del

rue

et a

l. 20

11, [

36]

32A

sses

s CTP

cha

ract

erist

ics i

n pa

tient

s with

PD

AC

com

-pa

red

to h

ealth

y pa

ncre

atic

tis

sue

in 1

28-s

lice

CT

In P

DA

C, B

F en

BV

val

ues

are

sign

ifica

ntly

low

er

than

in h

ealth

y pa

ncre

atic

pa

renc

hym

a

Dia

gnos

isN

APa

thol

ogy

Del

rue

et a

l. 20

12, [

37]

19Ev

alua

te w

heth

er C

TP

can

disti

ngui

sh g

ener

al

path

olog

ies o

f the

pan

crea

s

CTP

is a

ble

to d

istin

guis

h di

ffere

nt p

ancr

eatic

pa

thol

ogie

s bas

ed o

n B

F an

d BV

. Sho

win

g po

tent

ial

for C

TP in

dia

gnos

is

Dia

gnos

isN

APa

thol

ogy

D’O

nofr

io e

t al.

2013

, [40

]32

Des

crib

e C

TP p

aram

eter

s of

loca

lly a

dvan

ced

PDA

C

and

eval

uate

cor

rela

tion

with

tum

or g

radi

ng

Sign

ifica

nt d

iffer

ence

is

foun

d be

twee

n hi

gh-g

rade

an

d lo

w-g

rade

tum

ors f

or

BV. C

TP c

an p

redi

ct tu

mor

gr

ade

Gra

ding

NA

Path

olog

y (g

radi

ng b

ased

on

diffe

rent

iatio

n)

Ham

dy e

t al.

2019

, [35

]21

Inve

stiga

te th

e us

e of

CTP

to

pre

dict

the

resp

onse

of

PD

AC

to c

hem

orad

io-

ther

apy

Hig

her b

asel

ine

BF

is a

pr

edic

tor o

f res

pons

e. C

TP

may

be

usef

ul to

pre

dict

hi

stopa

thol

ogic

al re

spon

se

to c

hem

othe

rapy

Trea

tmen

t res

pons

e pr

edic

-tio

n12

.4 ±

10.8

Path

olog

y af

ter r

esec

tion

Kan

del e

t al.

2009

, [27

]73

Eval

uate

who

le-o

rgan

per

fu-

sion

pro

toco

l of p

ancr

eas

and

anal

yze

perf

usio

n di

ffere

nces

bet

wee

n no

rmal

pa

ncre

as a

nd P

DA

C

PDA

C sh

ows s

igni

fican

t lo

wer

per

fusi

on c

ompa

red

to n

orm

al p

ancr

eas.

CTP

pe

rfus

ion

is fe

asib

le a

nd

show

s pot

entia

l as d

iagn

os-

tic to

ol

Dia

gnos

is10

.1Pa

thol

ogy

Kla

uss e

t al.

2012

, [28

]25

Eval

uate

CTP

for P

DA

C

usin

g th

e Pa

tlak

mod

el to

as

sess

per

fusi

on

CTP

usi

ng P

atla

k an

alys

is is

fe

asib

le. B

F, B

V, a

nd P

S ca

n be

hel

pful

to d

elin

eate

PD

AC

Dia

gnos

is, s

can

tech

niqu

e6.

3Pa

thol

ogy

Abdominal Radiology

1 3

Tabl

e 2

(con

tinue

d)

Aut

hor,

publ

icat

ion

year

, ci

tatio

nPa

tient

s with

PD

AC

(n =

)A

imC

oncl

usio

nC

ateg

ory

Rad

iatio

n do

se (m

Sv)

Gol

d st

anda

rd

Kon

no e

t al.

2020

, [44

]17

Eval

uate

a v

olum

etric

CTP

in

terle

aved

into

pan

crea

tic

mul

tipha

sic

CEC

T in

the

clin

ical

setti

ng

An

inte

rleav

ed p

roto

col f

or

panc

reat

ic C

TP p

rovi

des

high

-qua

lity

imag

ing

whi

le

requ

iring

low

er ra

diat

ion

dose

than

con

vent

iona

l m

etho

ds

Scan

tech

niqu

e5.

1 ± 0.

3C

ECT

(Qua

lity

com

paris

on)

Kov

ac e

t al.

2019

, [24

]44

To e

valu

ate

CTP

and

DW

I qu

antit

ativ

e pa

ram

eter

s of

PDA

C a

nd to

ass

ess c

or-

rela

tion

with

clin

icop

atho

-lo

gica

l fea

ture

s

BV a

nd B

F ar

e si

gnifi

cant

ly

low

er in

hig

h-gr

ade

tum

ors c

ompa

red

to lo

w-

grad

e tu

mor

s. C

TP c

ould

im

prov

e as

sess

men

t of

PDA

C w

ith p

ossi

bilit

y of

gr

adin

g

Gra

ding

NA

Path

olog

y

Li e

t al.

2013

, [32

]46

Expl

ore

the

feas

ibili

ty o

f lo

w-d

ose

who

le-o

rgan

C

TP o

f pan

crea

s in

clin

ical

ap

plic

atio

n

Dos

e re

duct

ion

in C

TP is

fe

asib

le. B

F an

d BV

are

si

gnifi

cant

ly d

iffer

ent

betw

een

PDA

C a

nd n

orm

al

panc

reas

Dia

gnos

is <

70 k

g: 3

.6 >

70 k

g: 4

.9Pa

thol

ogy

Li e

t al.

2015

, [26

]20

Inve

stiga

te th

e va

lue

of lo

w-

dose

CTP

inte

grat

ed w

ith

dual

-ene

rgy

CT

in d

iagn

os-

ing

PDA

C

BF

and

BV a

re si

gnifi

cant

ly

diffe

rent

bet

wee

n PD

AC

an

d pa

ncre

atic

par

en-

chym

a. L

ow-d

ose

CTP

ca

n pr

ovid

e fu

nctio

nal

info

rmat

ion

Dia

gnos

is, s

can

tech

niqu

e4.

8–8.

4Pa

thol

ogy

Lu e

t al.

2011

, [31

]64

Inve

stiga

te 6

4-sl

ice

CTP

in

patie

nts w

ith P

DA

C a

nd

mas

s-fo

rmin

g ch

roni

c pa

ncre

atiti

s

CTP

can

hel

p to

dist

ingu

ish

PDA

C fr

om m

ass-

form

ing

chro

nic

panc

reat

itis.

BF

and

BV a

re lo

wer

in P

DA

C

com

pare

d to

pan

crea

titis

Dia

gnos

is4.

8–8.

4Pa

thol

ogy

Nis

hika

wa

et a

l. 20

14, [

42]

30In

vesti

gate

the

rela

tions

hip

betw

een

prog

nosi

s and

per

-fu

sion

in ti

ssue

surr

ound

-in

g PD

AC

usi

ng C

TP

Patie

nt p

rogn

osis

may

be

rela

ted

to p

erfu

sion

in

panc

reat

ic ti

ssue

adj

acen

t to

PD

AC

Trea

tmen

t res

pons

e pr

edic

-tio

nN

ASu

rviv

al d

ays

O’M

alle

y et

 al.

2020

, [25

]57

To e

valu

ate

the

feas

ibili

ty

of C

TP c

ombi

ned

with

ro

utin

e m

ultip

hase

 CEC

T in

PD

AC

 (int

erle

aved

pr

otoc

ol)

Com

bini

ng C

TP w

ith C

ECT

usin

g a

sing

le-c

ontra

st in

ject

ion

is fe

asib

le. P

erfu

-si

on p

aram

eter

s are

in li

ne

with

lite

ratu

re

Scan

tech

niqu

e10

.2C

ompa

rison

with

lite

ratu

re

refe

renc

e va

lues

Park

et a

l. 20

09, [

41]

17D

eter

min

e w

heth

er C

TP

para

met

ers c

an b

e us

ed to

pr

edic

t res

pons

e to

che

mo-

radi

othe

rapy

PDA

C w

ith h

ighe

r pre

-tre

atm

ent p

erm

eabi

lity

resp

onds

bet

ter t

o ch

emo-

radi

othe

rapy

Trea

tmen

t res

pons

e pr

edic

-tio

nN

AR

ECIS

T cr

iteria

Abdominal Radiology

1 3

Tabl

e 2

(con

tinue

d)

Aut

hor,

publ

icat

ion

year

, ci

tatio

nPa

tient

s with

PD

AC

(n =

)A

imC

oncl

usio

nC

ateg

ory

Rad

iatio

n do

se (m

Sv)

Gol

d st

anda

rd

Skor

nitz

ke e

t al.

2019

, [29

]19

Cal

cula

te C

TP p

aram

eter

s ba

sed

on q

uant

itativ

e io

dine

map

s usi

ng d

ual-

ener

gy C

T

CTP

par

amet

ers c

an b

e ca

lcul

ated

usi

ng d

ual-

ener

gy io

dine

imag

es.

Mea

sure

men

t acc

urac

y is

no

t im

prov

ed c

ompa

red

to

regu

lar C

TP

Scan

Tec

hniq

ue8.

01Pa

thol

ogy

Schn

eew

eiβ

et a

l. 20

16, [

39]

48Ev

alua

te in

terc

hang

e-ab

ility

of C

TP p

aram

eter

s ob

tain

ed u

sing

diff

eren

t ki

netic

mod

els i

n PD

AC

Sign

ifica

nt d

iffer

ence

s in

perf

usio

n pa

ram

eter

s are

ob

tain

ed u

sing

diff

eren

t ki

netic

mod

els;

how

-ev

er, m

agni

tude

of t

hese

pa

ram

eter

s is c

orre

late

d.

Para

met

ers d

o no

t sho

w

sign

ifica

nt d

iffer

ence

s for

hi

stolo

gica

l sub

grou

ps

Kin

etic

mod

els,

grad

ing

7.0(

mal

e)7.

1(fe

mal

e)Pa

thol

ogy

Tan

et a

l. 20

09, [

34]

27Fe

asib

ility

of l

ow-d

ose

who

le-p

ancr

eas i

mag

ing

utili

zing

64-

slic

e C

TP

BF

and

tissu

e pe

ak sh

ow

sign

ifica

nt d

iffer

ence

s be

twee

n PD

AC

and

pa

ncre

atic

par

ench

yma.

Re

duci

ng n

umbe

r of

acqu

isiti

ons d

oes n

ot si

g-ni

fican

tly c

hang

e pe

rfus

ion

para

met

ers

Dia

gnos

is13

.5 ±

0.5

Path

olog

y

Xu

et a

l. 20

09, [

23]

40Ex

plor

e C

TP c

hara

cter

istic

s of

nor

mal

pan

crea

s and

pa

ncre

atic

ade

noca

rcin

oma

BV, B

F, a

nd P

S in

PD

AC

are

si

gnifi

cant

ly lo

wer

com

-pa

red

to n

orm

al p

ancr

eas.

Perf

usio

n is

low

er to

war

ds

cent

er o

f the

tum

or

Dia

gnos

isN

APa

thol

ogy

Yada

v et

 al.

2016

, [33

]42

Eval

uate

the

use

of C

TP in

di

ffere

ntia

ting

PDA

C fr

om

mas

s-fo

rmin

g ch

roni

c pa

ncre

atiti

s

BF,

BV,

and

PS

are

sig-

nific

antly

low

er in

PD

AC

co

mpa

red

to c

hron

ic

panc

reat

itis a

nd n

orm

al

panc

reas

. CTP

can

serv

e as

to

ol in

dia

gnos

is to

diff

er-

entia

te P

DA

C fr

om c

hron

ic

panc

reat

itis

Dia

gnos

isN

APa

thol

ogy

Abdominal Radiology

1 3

tumor grades. In addition, a ROC curve analysis was per-formed to assess the prediction of tumor grade; Kovac et al. calculated an AUC of 0.940 for BF and 0.977 for BV, while D’Onofrio et al. calculated an AUC of 0.798 for BV [24, 40]. Perfusion parameters for the different grades can be found in Table 3.

In the third study, tumors were graded in three groups: well differentiated, moderately differentiated, and poorly dif-ferentiated. Using both deconvolution and Patlak combined with Max slope to calculate BF, BV, and PS, no significant differences between the three groups of pathological grade were found [39].

Treatment response prediction

Two studies investigated the role of CTP as a predictor of treatment response to neoadjuvant chemoradiotherapy with a total of 38 included patients [35, 41]. In both studies, treatment included 45–50,4 Gy radiation in 25–28 fractions and combined gemcitabine-based chemotherapy. Hamdy et al. classified response based on histology of the resection specimen after chemoradiotherapy, whereas Park et al. used the RECIST criteria on conventional CECT after 3 months

to assess treatment response; both studies performed CTP before treatment. Hamdy et al. reported a higher pre-treat-ment BF for responders compared to non-responders (44 vs. 28 mL/100 g/min, p = 0.04), whereas PS values were similar [35]. Pre-treatment perfusion measurements of Park et al. showed a significantly higher permeability in respond-ers compared to non-responders (50.8 vs. 19.0 mL/100 mL/min, p = 0.01) [41]. In both studies, pre-treatment BV was higher in responders compared to non-responders, although not significant.

Hamdy et al. performed a follow-up CTP after chemo-radiation therapy, 7 weeks after baseline CTP. Both BF (p = 0.04) and BV (p = 0.01) increased significantly in responders after chemoradiotherapy compared to baseline CTP). In non-responders, a non-significant increase in BF (p = 0.06) and BV (p = 0.06) was reported [35]. Table 4 pro-vides an overview of the perfusion parameters of responders and non-responders.

Instead of treatment response, another study performed a prediction of survival based on CTP. Perfusion values in peritumoral tissue directly adjacent to tumor tissue were assessed, resulting in a correlation between higher peritu-moral blood flow and shorter survival (p = 0.004) [42].

Fig. 1 Prisma-2015 flowchart of the study selection process

Records iden�fied through database searching(n = 881)

Screen

ing

Includ

edEligibility

Iden

�fica�

on

Removed duplicates(n = 274)

Records screened(n = 607)

Records excluded(n = 578)

Full-text ar�cles assessed for eligibility

(n = 29)Full-text ar�cles excluded (n = 8):

- Non-PDAC study popula�on (n=3)- Duplicate study par�cipants (n=3)- No perfusion parameters reported (n=2)

Studies included in qualita�ve synthesis

(n = 21)

Abdominal Radiology

1 3

Scanning protocols

In five studies, the main goal was the evaluation of the CTP scan technique for pancreatic cancer. A novel scanning method of an interleaved CTP protocol, where the perfusion acquisition was interleaved with a diagnostic multiphase contrast CECT was introduced in 2013 [43]. This method requires only one contrast bolus, instead of two separate boluses for the perfusion scan and diagnostic scan, allow-ing for a ‘one-stop-shop’ approach [25, 43, 44]. Two studies demonstrated that simultaneous acquisition of perfusion and high-quality diagnostic images with a single contrast bolus was feasible without difference in quality compared to con-ventional CECT [25, 44].

Three studies focused on the use of dynamic dual-energy CT acquisitions to calculate perfusion parameters. Li et al. combined both techniques by performing a dual-energy CT after a CTP scan, using the time–attenuation curve to improve the timing of the dual-energy CT [26]. Skornitzke et al. calculated BF based on DECT iodine enhancement images. However, these CTP maps did show a significant improvement compared to conventional acquisitions [29].

Bao et al. showed a good correlation of iodine concentration with both BF and BV, indicating the potential of dual-energy CT to reflect hemodynamic changes using a lower radiation dose [30]. However, the sensitivity to discriminate PDAC from non-tumorous pancreatic parenchyma was higher using CTP parameters with an AUC of 0.971 and 0.958 for BF and BV, compared to AUC of 0.842 for dual-energy-based iodine maps.

Kinetic models

In the reviewed articles, calculation of perfusion param-eters is performed using three main kinetic models: Max slope (one compartment), Patlak (two compartment), and deconvolution.

The maximum slope model assumes a single compart-ment to estimate the BF using the maximum slope of the time–attenuation curve. In addition, semi-quantitative parameters can be deduced from this time–attenuation curve, like peak enhancement compared to baseline and time to peak [45]. The single-compartment model assumes the

Fig. 2 Mean and standard devi-ation of blood flow of tumor (PDAC) and non-tumorous pancreatic parenchyma in all studies sorted by kinetic model. BF in tumor tissue is lower compared to non-tumorous pan-creas parenchyma in all studies. *Patlak model was reported in these studies. However, this model solely is not able to calculate BF

Abdominal Radiology

1 3

absence of venous outflow, therefore perfusion parameters as BV, and PS cannot be estimated [46].

The standard Patlak plot is a linear graphical represen-tation of a two-compartment model, which assumes the distribution of injected contrast agent over two well-mixed compartments. The model is based on an irreversible transfer of contrast agent from the intravascular to the extravascular

compartment, allowing estimations of the blood volume and permeability based on the linear part of the Patlak plot [47–49].

In the deconvolution method, the time–attenuation curve of the tissue is assumed to be the convolution between the arterial input function and the impulse residue function. This last curve is a theoretical representation of

Fig. 3 Mean and standard devi-ation of blood volume of tumor (PDAC) and non-tumorous pancreatic parenchyma in all studies sorted by kinetic model. BV in tumor tissue is lower compared to non-tumorous pan-creas parenchyma in all studies. *Maximum slope model was reported in these studies. How-ever, this model solely is not able to calculate BV

Fig. 4 Mean and standard deviation of vascular permeabil-ity surface area product (PS) of tumor (PDAC) and non-tumor-ous pancreatic parenchyma in studies sorted by kinetic model. *Maximum slope model was reported in these studies. How-ever, this model solely is not able to calculate PS

Abdominal Radiology

1 3

the fraction of contrast medium that remains in the tissue and can be calculated by deconvolution. On the basis of this impulse residue function, the BF, BV, and MTT are approximated [50–52].

Mean perfusion parameters in PDAC and non-tumor-ous pancreatic tissue as included in this review show a wide variance as visible in Figs. 2, 3, and 4. When studying the differences between the models, mean BF values calculated with the maximum slope model were significantly lower than using the deconvolution method [20.4 ± 9.7 mL/min/100 g and 36.9 ± 15.6 mL/min/100 g (p < 0.004)] [39]. BV values calculated with the decon-volution method resulted in significant higher values than with the Patlak model [7.3 ± 4.7  mL/100  g vs. 5.6 ± 5.5 mL/100 g (p < 0.001)], in contrast to the values found for PS [12.4 ± 8.2 mL/100 g/min for deconvolution vs 18.9 ± 9.8 mL/100 g/min for Patlak, (p < 0.001)]. How-ever, comparing perfusion parameters of both models, a good correlation was found between Deconvolution and

Max slope + Patlak parameters using ICC and Pearson lin-ear correlation coefficient [39].

Risk of bias

Figure 5 shows the results of risk of bias and concerns about applicability using the QUADAS-2 tool. Overall stud-ies show a low risk of bias; however, the index test is not always accurately reported, especially concerning the use of the kinetic model. Some studies show an inconsistency, as reported perfusion parameters cannot be calculated from the presented kinetic model, and these studies were marked as high risk in bias for the index test.

Patient flow and timing between CTP and reference stand-ard were reported poorly in almost all studies. For QUA-DAS-2 per study, see Fig. 4.

Table 3 For different histopathological grading of PDAC mean/median, BF values are reported in (mL/100 g/min), BV is reported in (mL/100 g), and PS is reported in (mL/100 g/min)

Kovac and D’Onofrio classified both moderate- and well-differentiated lesions as low gradea Significant differences between pathological grading groups. Grade was high (poorly differentiated), inter-mediate (moderately differentiated), or low (well differentiated)b Median values, rest of the table report mean values

Study Histopathological grade

High Intermediate Low grade

Kovac et al. [24] BF: 17.45 ± 4.1a

BV: 2.66 ± 1.0aBF: 28.5 ± 7.7a

BV: 5.5 ± 1.4a

D’Onofrio et al. [40] BF: 5.9b

BV: 11.3a, bBF: 8.9b

BV: 19a, b

Schneeweiβ et al. [39](Max Slope + Patlak)

BF: 21.9 ± 10.4BV: 5.5 ± 4.5PS: 11.5 ± 6.4

BF: 21.9 ± 10.4BV: 5.5 ± 4.5PS: 21.0 ± 10.2

BF: 20.6 ± 8.6BV:8.9 ± 11.3PS:19.3 ± 4.5

Schneeweiβ et al. [39](Deconvolution)

BF: 35.6 ± 13.9BV: 6.1 ± 3.9PS: 11.9 ± 7.1

BF: 37.7 ± 16.6BV: 7.9 ± 5.5PS: 13.7 ± 8.8

BF: 33.5 ± 10.3BV: 6.4 ± 1.3PS: 11.5 ± 6.4

Table 4 Mean/median perfusion parameters of responders and Non-responders during CTP performed at baseline and follow-up after chemora-diotherapy

Parameters of Hamdy reported as median values, parameters of Park reported as mean resultsa Significant difference between responder and non-responderb Significant difference compared to baseline perfusion parameters of responders. Parameters of Hamdy reported as median values, parameters of Park reported as mean results

Study Baseline responder Baseline non-responder FU responder FU non-responder

Hamdy et al. [35] BF: (mL/100 g/min): 44a

BV: (mL/100 g): 4.3PS: (mL/100 g/min): 25

BF: 28a

BV: 2.0PS: 20

BF: 54b

BV: 6.8b

PS: 32

BF: 43BV: 4.8PS: 28

Park et al. [41] Permeability(mL/100 mL/min): 50.8 ± 30.5a

BV (mL/100 mL): 5.7 ± 3.0

Permeability: 19.0 ± 10.9a

BV: 4.1 ± 1.7

Abdominal Radiology

1 3

Discussion

Main study findings

The results from this systematic review show that CTP can accurately distinguish PDAC from non-tumorous pancreatic parenchyma using perfusion parameters calculated with a kinetic model. There is a clear consensus that PDAC can be distinguished from non-tumorous pancreatic parenchyma with a significantly lower BF and BV in PDAC compared to non-tumorous pancreatic parenchyma. Only a few studies showed a significant difference in PS between PDAC and non-tumorous pancreatic parenchyma, but the mean PS for PDAC was consistently lower. Although not studied pro-spectively, perfusion parameters seem to be able to improve the detection of PDAC that is visually isoattenuating on biphasic CECT.

For grading, CTP can be used as an additional imaging biomarker, which is an important prognostic variable of sur-vival in PDAC. In two studies, a significant difference was found between high-grade tumors and low-grade tumors for BV, and in one of these studies, BF also showed a significant difference [24, 40]. In a third study, no significant difference could be found between three pathological grades using BF, BV, and permeability [39]. There is no clear consensus for the use of CTP as a biomarker for the pathological grade. Nonetheless, two out of three studies show significant dif-ferences between grades. Large clinical studies are needed to correlate perfusion parameters to histological grade on the resection specimen.

Treatment assessment using CTP was investigated in two studies. Pre-treatment BF and permeability showed to be a good indicator of histopathological response to chemora-diotherapy [35, 41]. Furthermore, CTP was also performed to assess the effects after chemoradiation therapy. Both responders and non-responders showed an increase in blood flow and blood volume, but only the increase in respond-ers was significant. The microenvironment of PDAC could provide an explanation for these findings, as PDAC has a stroma-rich tumor environment with high intratumoral pres-sure [52]. This could result in impaired perfusion, eventually impeding the delivery of oxygen and chemotherapy to tumor cells [53]. In tumors with less vessel restriction, reflected by higher baseline perfusion, chemotherapy is better able to penetrate the tissue. Both prediction and assessment of chemoradiotherapy response show promising results which reflect microenvironmental differences. Clinical studies are needed to assess the use of CTP in both baseline and follow-up of treatment, to evaluate CTP as biomarker in treatment assessment.

Kinetic models/scan parameters

Perfusion parameters strongly depend (up to 30%) on the applied kinetic model and are not directly interchangeable, as shown in a variety of other cancers [51]. Of the included studies, 7 out of 21 used a deconvolution algorithm, 8 used a max-slope algorithm, and in 6 studies, a Patlak analysis was reported. Four studies reported a combination of the compartment models: Max-slope and Patlak analysis. The reported perfusion parameters display a wide range of varia-bility between different kinetic models and perfusion param-eters do not always correspond with the reported model. In six articles, BF values were described, even though the reported model was the Patlak model. An explanation could be that some software combines the Patlak and the max-slope models, using the latter to determine the BF. Further-more, three studies report BV and two PS, although only a max-slope model was mentioned.

Fig. 5 Quality assessment of diagnostic accuracy studies (QUA-DAS-2)

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In this review, three frequently used kinetic models are described; variations in these models exist, but use is not clearly reported in the literature. The assumptions of the kinetic model influence the calculated quantitative param-eters differently. Maximum slope assumes a single compart-ment and, therefore, no venous outflow out of the tissue. The advantage of this model is the short acquisition time and the simplicity of mathematics. The latter also presents a disadvantage as the correlation between the assumptions made and true physiology is difficult. In all healthy tissue, venous outflow is present; therefore, the true BF is higher than calculated with this model.

The standard Patlak model quantifies the exchange between two compartments: the intravascular and extravas-cular compartments. This linear model assumes that the back-flux of contrast agent from the extravascular to the intravascular compartment is negligible [49]. This assump-tion can be applied only during the first pass of contrast agent in tissue and depends on the relative magnitude of blood flow and permeability surface area. However, as PDAC is a hypovascular tumor, the magnitude of blood flow could, therefore, be inadequate to meet this assumption [49, 54]. To take the back-flux into account, a modified Patlak model has been developed, although this non-linear model is more difficult to implement [55, 56].

Deconvolution uses the arterial and time-attenuation curves to calculate the impulse residue function for the tis-sue. The advantage is that BF, BV, and MTT can be calcu-lated directly with a single model. It is assumed that contrast material is nondiffusible out of the vessels which is not an accurate theory, as there is leakage into the interstitial space [50].

All three models use different assumptions, which do not always accurately reflect pancreatic (tumor) tissue physi-ology. It is impossible to exactly modulate the kinetics of a contrast agent in tissue, though optimization for specific indications has led to numerous tracer-kinetic models [57, 58]. The preferred model depends on the desired parameters, target area as well as on the acquisition protocol. Since reso-lution and noise can influence the quantification, sensitivity to noise could explain the lack of consensus on the more mathematically complex parameter PS.

The chosen acquisition and analysis methods strongly influence estimated perfusion parameters. Included stud-ies used a contrast dose in the range of 40–80 mL, with exception of studies using an interleaved protocol in which a weight-based contrast dose was used. The amount of con-trast agent volume (50 vs 100 mL) does not substantially change quantitative perfusion parameters for colorectal can-cer [59]. The reproducibility of CTP as assessed by Kauf-mann et al. showed an interscan variability in the range of 30% [60]. Respiratory motion during scanning is one of the causes for interscan variability, and motion correction

methods significantly improve the reproducibility of CTP [61]. Positioning and size of the measured region of interest (ROI) do influence the measured perfusion values. An ROI comprising the entire tumor diameter leads to more stable perfusion measurements, compared to a smaller ROI. As PDAC is known to be heterogeneous, an ROI in a single slice could introduce measurement bias. This is also high-lighted in two studies reporting an increase in perfusion val-ues towards the rim of the tumor [25, 36]. A 3D volume of interest would be a more reliable measurement and allows a better understanding of the whole tumor.

Limitations

For this systematic review, some limitations need to be addressed. First, the number of clinical studies performing CTP in PDAC is still low with too small study populations. The diagnostic accuracy of the technique is not compared to CECT in terms of diagnosis. Second, it is difficult to quantitively compare perfusion parameters of studies using different kinetic models, analysis software, ROI definitions, and scan parameters. As the diversity of the data influences the calculated parameters, no meta-analysis was performed. Third, poor reporting of applied kinetic models could ham-per the interpretation of some included studies. Most studies risks of bias were high or unclear, making the summarized evidence limited.

Future perspectives

CTP provides high spatiotemporal resolution data for quan-titative functional information about PDAC which could help in diagnosis, grading, and treatment prediction. The current use of CTP for PDAC is still limited mainly due to concerns regarding technique and knowledge. The amount of radiation for a CTP has been reduced due to improve-ments in detector efficiency and reconstruction algorithms. The additional information provided by CTP could help steer treatment decision and, therefore, seems to outweigh the risk of radiation.

There are several developments which could help to bring CTP into clinical practice. Advanced interleaved techniques make it possible to perform CTP during routine multiphase contrast-enhanced pancreatic CT using a single-contrast injection [25, 44]. In such a ‘one-stop-shop’ procedure, per-fusion information is acquired without extra time and cost for the patient and can be applied in oncologic imaging add-ing functional information. Furthermore, due to new multi-detector CT scanners, larger tissue volumes can be scanned, which facilitate perfusion evaluation of the whole tumors and their surroundings.

One of the barriers limiting widespread adoption seems the lack of reference values, scan standards, and validation.

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It is difficult to compare perfusion values across different scanners, kinetic models, software, and scan parameters, limiting the use of CTP as a quantitative imaging biomarker for clinical decision making. To increase the use of CTP, some steps need to be taken as described in the EIBALL cri-teria [62]. First, standardization of scan protocol and report-ing of CTP need to be established, enabling better compari-son of studies. In addition, perfusion parameters need to be validated with pathology assessment such as microvessel density, permeability, or aggressiveness markers. The latter allows a better understanding of quantitative values aiding in treatment response prediction and, therefore, precision treatment.

Improvement of post-processing also could lead to a more reliable assessment of perfusion parameters. Compartmental and deconvolution analysis are the most widely used kinetic models; however, there is no consensus regarding applicabil-ity for abdominal oncology. In this review, we showed that results among studies are not directly comparable. Kinetic models and CTP software are often not tailored and vali-dated for oncology. Because of the physiological differences, other perfusion models and parameters might be more useful to assess tumor characteristics or treatment response.

Novel analysis methods using artificial intelligence (AI) could help extracting diagnostic CTP information from time–intensity curves. AI can facilitate kinetic model-independent interpretation of CTP, reducing inter-observer bias and parameter variability. Radiomics can effectively combine all CTP parameters with spatial information to guide treatment of patients with PDAC [63]. These data-driven biomarkers and their potential to improve tumor characterization and treatment assessment are increasingly investigated [63–65]. A combination of CTP and radi-omic features already shows to improve the prediction of response in laryngeal cancer [66]. Furthermore, AI meth-ods and advanced filters could reduce noise in CTP images, improving the image quality and quantitative analysis. For instance, dynamic similarity filters not only are already in use for cardiac CTP but are also in development for abdomi-nal CTP [67]. These developments could facilitate clinical adoption and maximize impact by optimizing the analysis of CTP images regardless of acquisition and reconstruction parameters.

Conclusion

Quantitative CTP shows a potential benefit in PDAC diag-nosis and can serve as a tool for pathological grading and treatment assessment; however, clinical evidence is still limited. To improve clinical use, standardized acquisition and reconstruction parameters are necessary for the inter-changeability of the perfusion parameters. The use of an

interleaved CTP-CECT protocol followed by post-processing and AI-supported analysis could advance the use of CTP as a predictive biomarker for PDAC.

Supplementary Information The online version contains supplemen-tary material available at https:// doi. org/ 10. 1007/ s00261- 021- 03190-w.

Funding Partial financial support was received from the KWF Dutch Cancer Society (KWF:12034).

Declarations

Conflict of interest The authors have no relevant financial or non-fi-nancial interests to disclose.

Open Access This article is licensed under a Creative Commons Attri-bution 4.0 International License, which permits use, sharing, adapta-tion, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.

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